code: def mean_euclidean(
      detection: "Detection", tracked_object: "TrackedObject"
  ) -> float:
      """
      Average euclidean distance between the points in detection and estimates in tracked_object.
  
      $$
      d(a, b) = \\frac{\\sum_{i=0}^N ||a_i - b_i||_2}{N}
      $$
  
      Parameters
      ----------
      detection : Detection
          A detection.
      tracked_object : TrackedObject
          A tracked object
  
      Returns
      -------
      float
          The distance.
  
      See Also
      --------
      [`np.linalg.norm`](https://numpy.org/doc/stable/reference/generated/numpy.linalg.norm.html)
      """
      return np.linalg.norm(
          detection.points - tracked_object.estimate, axis=1
      ).mean()
  
imports: from abc import ABC, abstractmethod
  from functools import partial
  from logging import warning
  from typing import TYPE_CHECKING, Callable, List, Optional, Sequence, Union
  import numpy
  from scipy.spatial.distance import cdist
label_desc: Use image node_id 2 for calling a global function with example usage: mean_euclidean(detection, tracked_object) and returns: np